Epigenetics, the study of non-DNA sequence-related heredity, is at the epicenter of modern medicine because it can help to explain the relationship between an individual's genetic background, the environment, aging, and disease. The Center for the Epigenetics of Common Human Disease was created four years ago to begin to develop the interface between epigenetics and epidemiologic-based phenotype studies, recognizing that epigenetics requires new ways of thinking about disease. We used the reduced funding of the current grant cycle to create a highly interdisciplinary group of faculty and trainees, including molecular biologists, biostatisticians, epidemiologists, and clinical investigators. Working together, we have developed novel approaches to genome-wide DNA methylation (DNAm) analysis, allele-specific expression, and new statistical epigenetic tools. Using these tools, we discovered that most variable DNAm is in neither CpG islands nor proelationship between epigenetic variation, genetic variation, environment and phenotype. We will continue to pioneer genome-wide epigenetic technology that is cost effective for large scale analysis of population-based samples, applying our knowledge from the current period to second-generation sequencing for epigenetic measurement, including DNAm and allele-specific methylation. We will continue to pioneer new statistical approaches for quantitative and binary DNAm assessment in populations, including an Epigenetic Barcode. We will develop Foundational Epigenetic Epidemiology, examining: time-dependence, heritability and environmental relationship of epigenetic marks;heritability in MZ and DZ twins;and develop an epigenetic transmission disequilibrium test. We will then pioneer Etiologic Epigenetic Epidemiology, by integrating novel genome-wide methylation scans (GWMs) with existing Genome-Wide Association Study (GWAS) and epidemiologic phenotype data, a design we term Genome-Wide of disease.
- Most common human disease is caused by a combination of genetic, environmental, and epigenetic factors, the latter of which is non-sequence information that controls gene function and mediates the relationship between genes and the environment. We are creating the new field of epigenetic epidemiology by providing the experimental tools, statistical methods, and approaches to key barriers that have prevented incorporation of epigenetics into research on diseases such as bipolar disorder, autism and age-related illness.
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|Ladd-Acosta, Christine (2015) Epigenetic Signatures as Biomarkers of Exposure. Curr Environ Health Rep 2:117-25|
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|Jaffe, Andrew E; Storey, John D; Ji, Hongkai et al. (2013) Gene set bagging for estimating the probability a statistically significant result will replicate. BMC Bioinformatics 14:360|
|Reddy, Karen L; Feinberg, Andrew P (2013) Higher order chromatin organization in cancer. Semin Cancer Biol 23:109-15|
|Liu, Yun; Aryee, Martin J; Padyukov, Leonid et al. (2013) Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol 31:142-7|
|Timp, Winston; Feinberg, Andrew P (2013) Cancer as a dysregulated epigenome allowing cellular growth advantage at the expense of the host. Nat Rev Cancer 13:497-510|
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